Grocery & Convenience

E‑grocery warehouse automation

Logio partnered with one of France's largest food retailers to design a scalable automation concept for their e‑commerce warehouse, combining feasibility analysis, technology comparison, and a full business case.

Outcome

The retailer's manually operated e‑grocery warehouses were hitting capacity limits as online order volumes grew. Logio delivered a data‑backed automation roadmap that unlocks a 400% gain in picking productivity, cuts order lead time by 20 minutes, and supports up to 5x capacity growth through phased technology deployment.

Picking productivity

+0 %

Order progress through warehouse

-0 min

Scalable warehouse capacity

x0

Initial challenge

The retailer launched online grocery sales, but its e‑commerce warehouses relied entirely on manual processes. As order volumes grew, the operation was approaching its throughput ceiling, with no clear path to scale.

Project goal

Create a long‑term operating model for the e‑commerce warehouse that protects the investment even under several‑fold growth in online sales, giving management a data‑backed foundation for their automation decision.

Solution

From manual bottleneck to scalable automation blueprint

Description: Logio mapped the retailer's current warehouse operations, modeled future capacity needs under multiple growth scenarios, and evaluated automation technologies to deliver an investment‑ready recommendation.

01

Current‑state analysis and future capacity modeling

Logio analyzed assortment, inventory, and order data over time and defined future capacity requirements, separately for dry goods, chilled goods, and in‑house production. The study modeled growth scenarios up to 5x current online volume, each with its own capacity and investment implications.

02

Process mapping, material flow, and product placement analysis

The team mapped core warehouse processes and material flows as the foundation for the future‑state design. Data analysis covered product placement by turnover rate and co‑picking patterns. The in‑house production process, previously non‑serial and cost‑intensive despite being a competitive differentiator, was also optimized.

03

Automation concept design

Logio compared multiple automation levels, from incremental process changes to full automation of receiving, storage, and picking. Technologies evaluated included shuttle systems, robotic shuttles, and cube‑based storage. Each concept included a proposed warehouse layout with process areas, handling technology, and phased expansion scenarios.

04

Business case and decision framework

Each variant was evaluated end‑to‑end: not just technology cost, but total operational impact. Deliverables included a business case, ROI timeline, total cost of ownership (TCO), layouts, phased rollout scenarios, staffing requirements, risk analysis, and an indicative implementation and maintenance schedule. Logio recommended the most suitable solution based on these findings.

Solutions implemented

OPEX, CAPEX and ROI Calculations

Process Mapping & Analysis

Business Case & Feasibility Study

Impact

A clear path from manual ceiling to automated growth

Data‑based investment decisions

into automation for management.

Scalable warehouse automation concept

based on the future online sales growth strategy.

400% increase in picking productivity

in the final recommended AutoStore variant.

Reduction of expedition staff by 3 FTE

only based on a process change.

Reduction of labor intensity in own production by up to 40%

due to the narrowing of the product portfolio and mass production.

It was essential to view the entire warehouse as a single entity during the design process. This allowed us to come up with a comprehensive solution and eliminate bottlenecks in secondary processes, instead of just passively working with their limitations.

Adam Zdvihal

Project Manager, Logio

Ready to future‑proof your e‑commerce logistics?

If your online grocery operation is outgrowing its manual setup, we can help you find the right automation path. Let's talk about turning warehouse constraints into scalable capacity.

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